Thursday, June 23, 2016

I came across this profound TED Talk this morning. Highly recommended.

It would be easy to dismiss the talk as "Interesting, but of little value to us.. our system is already doing so much better than theirs".

Improvement Process

On the other hand I think it has profound lessons for us, especially how they implemented their improvements

Be clear about what was really happening here and now*

Establish a specific shared goal

Identify the current issues (constraints) in relation to the goal

Create your own solutions (address the constraints)

Change the system from a hierarchy to a network

If only we all did the same!!!

Everyone's job

Incidentally the strategy fits nicely with the "job description" that applied to everyone at Riverside: staff, students, parents, visitors...

Know what is happening

Work with others to improve what is happening

Make it easier for the next person to do well

And finally, the Talk, and the above notes are consistent with the application of Complexity Theory. Perhaps without knowing it Seema and her team actually treated their education system as a complex adaptive system rather than as a simple linear (top-down) system.

[* Not trying to work back from some remote idealised future "reality"]

As a result it is not possible to accurately predict the outcomes, especially in the longer term. This is true for all complex systems (e.g., the weather). Nor is it easy to replicate outcomes because "best practices" are situated and not readily transferred. In complex systems (such as education) knowledge, actions (practices) and arrangements have be continually constructed and reconstructed.

Teaching is largely about discovering and applying what is helpful to the students as they endeavour to learn. That is, teaching is more about the provision of scaffolding that nurtures the emergence of learning. And this works best when teachers and learners work together to customise the student's learning. Notions of "R&D" are more useful than notions of education as "production". Schools work better as purposeful communities than as "factories".

Improving education

Top-down initiatives can work well in linear systems. However, improving complex adaptive systems such as education is best done by nurturing the emergence of desirable developments. This can be done by

learning from small safe-fail experiments - efforts that will not do any significant damage if they fail.

Learning from success

Learning from successful experiments needs to be done cautiously. To conclude from a successful experiment that the method can be widely applied is to make the error of retrospective coherence. Being able to give an account of why/how something was achieved does not mean that it can be readily replicated.

Complex adaptive systems are subject to the starting conditions. In education these including history, culture, environment... Engineering best practices can be readily transferred - with natural physical phenomena cause and effect are consistent over place and time. The same cannot be said for teaching and learning - cause and effect are not universally consistent and may be distant from each other in place and time.

Evidence-based practices

Unfortunately many top-down initiatives are based on mandating the use of evidence-based practices, as if they work like engineering practices. The notion of "evidence-based practices" is usually flawed by retrospective coherence, and frequently leads to the injustice of "They did it, why can't you?" Education has a history strewn with examples of initiatives that failed despite their origins being based on prior successful examples.

Tuesday, June 21, 2016

As a follow up on yesterday's post it may be helpful to clarify two major notions of systems.

1. Linear systems: input=>process=>output

The most common notion of a system is one in which input is processed to create an output. These systems are often described as linear and can be as simple as a light circuit:- the input of electricity flowing through the circuit causes the globe to output light. The process may involve the heating of a filament the activation of some other source of light. Combining such systems, and building in feedback loops, can create quite complicated devices such as airliners, computers etc. In linear systems, cause and effect are consistent over place and time such that outputs can be replicated. That is, outputs are predictable.

2. Complex adaptive systems: emergent, self organising...

Complex adaptive systems are the second major type of system. The outputs emerge from the interaction of the elements within the system and the interaction of the system with its environment. While patterns may emerge overtime outputs cannot be predicted accurately, especially over the long term. Weather, social systems and ecosystems are common examples of complex adaptive systems.

As social entities, schools are complex adaptive systems. However they can often be treated, at least in part, AS IF, they were linear systems. To do so is reasonable under certain conditions, namely that the patterns of interaction involved a stable. Hence Deming's advice to “first stabilize the system” before trying to improve it.

Complex adaptive systems are vulnerable to disruption but may also be highly resilient as a result of their capacity to be self organising and their wide range of possible responses. (see Requisite Variety).

Systems thinking and its limitations

Systems thinking as it applies to linear systems, offers a range of very useful approaches and tools for school improvement. However it is critical to understand the limitations of systems thinking and the assumptions made being in its application to specific circumstances.

A systems models is a kind of map of the system and it is important to remember that "A map is not the territory".

Monday, June 20, 2016

When faced with something challenging and complex, our natural inclination is to treat it as if it was linear. And under certain conditions this can be useful. The danger is that we may begin to confuse our "linear models" reality.

Schooling is a complex endeavour - one that is often complicated and uncertain, especially in relation to the processes, participants and the contexts in which it occurs.

Consider the following simple linear model of schooling:

The model is a reasonable summary of the commonly held view of how the school system works. Because of its general nature the model "works" despite the variations that that may apply. For example, government policy and funding varies considerably from school to school and government to government.

Cause and effect

In terms of time and activity the general flow of cause and effect is from left to right. Since most students are children they tend to have little or no responsibility for the effectiveness of the system. This "justifies" the widespread use of of student achievement (effect = learning outcomes) as an measure of school performance as cause.

Also cause and effect can be remote in both time and place - a cause may not be directly related to a effect (see 5 Whys). For example, the model does not indicate the extent to which government policies and funding enable/constrain the capacity of schools to provide teaching matched to the needs of their students in real-time.

Too simplistic

The model is too simplistic in that it does not show any feedback loops nor does it give any indication of strength of flows between its elements.

Nor does the model show all key participants many of which play an important role in the effectiveness or otherwise of the system.

A useful starting point
The model is quite inadequate to properly explain how schooling happen. On the other hand it does represent the general discourse quite well and hence could be provide a useful starting point for the development of a systems approach to school improvement. And a systems approach is needed to better inform decision making at all levels.